Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and delivers: it discloses pricing (FREE, no per-run charge), auth requirements (Apify token via Bearer), rate limits (60 calls/min/IP), and return shape (0-7 score, fixes, llms.txt draft, full report in one response, no pagination). This is above the bar expected for an unannotated read tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose and the key alternative are front-loaded in the first two sentences, and the trailing operational facts (pricing, auth, rate limit, no pagination) are compressed into short clauses. It is dense but nearly every clause carries actionable information; a minor trim of the pricing/auth restatement would tighten it further.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema or annotations exist, yet the description compensates fully: it explains the return value (0-7 score plus fixes and an llms.txt draft), scope boundaries, the sibling alternative, auth, rate limits, and response shape. An agent has everything needed to call and interpret this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and both parameters are well documented in the schema itself. The description reinforces behavior (fetching homepage, /llms.txt, /robots.txt; generating an llms.txt draft) but adds no syntax or format detail beyond what the schema already provides, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Check) and resource (a website's AI visibility) and enumerates the 7-criteria AEO audit contents (JSON-LD, llms.txt, AI bots in robots.txt). It explicitly distinguishes itself from the sibling local_presence_audit, so an agent can route correctly without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-to-use trigger ('when you need to know if a site can be cited by ChatGPT, Perplexity or Claude') and a hard exclusion with an alternative: 'This audits ONLY the website... use local_presence_audit instead when you need the full local-business picture'. The when/when-not/alternative triad is fully covered.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.